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This paper presents a new event-based method for detecting and tracking features from the output of an event-based camera. Unlike many tracking algorithms from the computer vision community, this process does not aim for particular…

Computer Vision and Pattern Recognition · Computer Science 2018-11-20 Laurent Dardelet , Sio-Hoi Ieng , Ryad Benosman

Event cameras are paradigm-shifting novel sensors that report asynchronous, per-pixel brightness changes called 'events' with unparalleled low latency. This makes them ideal for high speed, high dynamic range scenes where conventional…

Computer Vision and Pattern Recognition · Computer Science 2020-08-25 Timo Stoffregen , Cedric Scheerlinck , Davide Scaramuzza , Tom Drummond , Nick Barnes , Lindsay Kleeman , Robert Mahony

Event camera, a novel neuromorphic vision sensor, records data with high temporal resolution and wide dynamic range, offering new possibilities for accurate visual representation in challenging scenarios. However, event data is inherently…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lin Zhu , Ruonan Liu , Xiao Wang , Lizhi Wang , Hua Huang

This paper introduces a framework of gesture recognition operating on the output of an event based camera using the computational resources of a mobile phone. We will introduce a new development around the concept of time-surfaces modified…

Computer Vision and Pattern Recognition · Computer Science 2020-04-29 Jean-Matthieu Maro , Ryad Benosman

We present ContinuityCam, a novel approach to generate a continuous video from a single static RGB image and an event camera stream. Conventional cameras struggle with high-speed motion capture due to bandwidth and dynamic range…

Computer Vision and Pattern Recognition · Computer Science 2025-04-25 Ziyun Wang , Friedhelm Hamann , Kenneth Chaney , Wen Jiang , Guillermo Gallego , Kostas Daniilidis

Objective: The Mapper algorithm is a qualitative method in topological data analysis that constructs graphs from point clouds by combining dimensionality reduction and clustering techniques. The aim of this study is to apply Mapper,…

Quantitative Methods · Quantitative Biology 2026-04-22 Aina Ferrà Marcús , Carles Casacuberta , Josep Vives , Joan Guich , Gerard Amorós-Figueras , Jose M. Guerra

We introduce EDS, a direct monocular visual odometry using events and frames. Our algorithm leverages the event generation model to track the camera motion in the blind time between frames. The method formulates a direct probabilistic…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Javier Hidalgo-Carrió , Guillermo Gallego , Davide Scaramuzza

An event-based camera outputs an event whenever a change in scene brightness of a preset magnitude is detected at a particular pixel location in the sensor plane. The resulting sparse and asynchronous output coupled with the high dynamic…

Computer Vision and Pattern Recognition · Computer Science 2023-08-02 Loïc J. Azzalini , Emmanuel Blazquez , Alexander Hadjiivanov , Gabriele Meoni , Dario Izzo

We propose DeepExplorer, a simple and lightweight metric-free exploration method for topological mapping of unknown environments. It performs task and motion planning (TAMP) entirely in image feature space. The task planner is a recurrent…

Robotics · Computer Science 2023-03-17 Yuhang He , Irving Fang , Yiming Li , Rushi Bhavesh Shah , Chen Feng

Event cameras are biologically-inspired sensors that gather the temporal evolution of the scene. They capture pixel-wise brightness variations and output a corresponding stream of asynchronous events. Despite having multiple advantages with…

Computer Vision and Pattern Recognition · Computer Science 2019-12-11 Stefano Pini , Guido Borghi , Roberto Vezzani

Event cameras are bio-inspired vision sensors that output pixel-level brightness changes instead of standard intensity frames. These cameras do not suffer from motion blur and have a very high dynamic range, which enables them to provide…

Computer Vision and Pattern Recognition · Computer Science 2018-04-06 Antoni Rosinol Vidal , Henri Rebecq , Timo Horstschaefer , Davide Scaramuzza

This study presents an automated topology optimization framework for designing pentamode acoustic metamaterials. It provides precise control over the material effective acoustic properties while minimizing the shear modulus to achieve…

Applied Physics · Physics 2026-03-03 Sebastiano Cominelli , Matteo Pozzi , Francesco Braghin

Schlieren imaging is an optical technique to observe the flow of transparent media, such as air or water, without any particle seeding. However, conventional frame-based techniques require both high spatial and temporal resolution cameras,…

Computer Vision and Pattern Recognition · Computer Science 2024-03-05 Shintaro Shiba , Friedhelm Hamann , Yoshimitsu Aoki , Guillermo Gallego

Event-based cameras are biologically inspired sensors that output events, i.e., asynchronous pixel-wise brightness changes in the scene. Their high dynamic range and temporal resolution of a microsecond makes them more reliable than…

Robotics · Computer Science 2021-07-13 Antea Hadviger , Igor Cvišić , Ivan Marković , Sacha Vražić , Ivan Petrović

Despite the promise of superior performance under challenging conditions, event-based motion estimation remains a hard problem owing to the difficulty of extracting and tracking stable features from event streams. In order to robustify the…

Computer Vision and Pattern Recognition · Computer Science 2024-01-18 Wanting Xu , Si'ao Zhang , Li Cui , Xin Peng , Laurent Kneip

In low-light conditions, capturing videos with frame-based cameras often requires long exposure times, resulting in motion blur and reduced visibility. While frame-based motion deblurring and low-light enhancement have been studied, they…

Computer Vision and Pattern Recognition · Computer Science 2024-08-28 Taewoo Kim , Jaeseok Jeong , Hoonhee Cho , Yuhwan Jeong , Kuk-Jin Yoon

This paper presents EROAM, a novel event-based rotational odometry and mapping system that achieves real-time, accurate camera rotation estimation. Unlike existing approaches that rely on event generation models or contrast maximization,…

Computer Vision and Pattern Recognition · Computer Science 2026-01-30 Wanli Xing , Shijie Lin , Linhan Yang , Zeqing Zhang , Yanjun Du , Maolin Lei , Yipeng Pan , Chen Wang , Jia Pan

Event cameras are sensors inspired by biological systems that specialize in capturing changes in brightness. These emerging cameras offer many advantages over conventional frame-based cameras, including high dynamic range, high frame rates,…

Computer Vision and Pattern Recognition · Computer Science 2023-09-04 Haodong Chen , Vera Chung , Li Tan , Xiaoming Chen

Event cameras are a paradigm shift in camera technology. Instead of full frames, the sensor captures a sparse set of events caused by intensity changes. Since only the changes are transferred, those cameras are able to capture quick…

Computer Vision and Pattern Recognition · Computer Science 2017-03-22 Christian Reinbacher , Gottfried Munda , Thomas Pock

Event cameras offer high temporal resolution and power efficiency, making them well-suited for edge AI applications. However, their high event rates present challenges for data transmission and processing. Subsampling methods provide a…

Computer Vision and Pattern Recognition · Computer Science 2025-05-28 Hesam Araghi , Jan van Gemert , Nergis Tomen
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